Data Organization in Spreadsheets: Glossary

Key Points

  • Good data organization is the foundation of any research project.

Formatting data tables in Spreadsheets
  • Never modify your raw data. Always make a copy before making any changes.

  • Keep track of all of the steps you take to clean your data.

  • Organize your data according to tidy data principles.

Formatting problems
  • Avoid using multiple tables within one spreadsheet.

  • Avoid spreading data across multiple tabs (but do use a new tab to record data cleaning or manipulations).

  • Record zeros as zeros.

  • Use an appropriate null value to record missing data.

  • Don’t use formatting to convey information or to make your spreadsheet look pretty.

  • Place comments in a separate column.

  • Record units in column headers.

  • Include only one piece of information in a cell.

  • Avoid spaces, numbers and special characters in column headers.

  • Avoid special characters in your data.

  • Record metadata in a separate plain text file.

Dates as data
  • Treating dates as multiple pieces of data rather than one makes them easier to handle.

Quality control
  • Always copy your original spreadsheet file and work with a copy so you don’t affect the raw data.

  • Use data validation to prevent accidentally entering invalid data.

  • Use sorting to check for invalid data.

  • Use conditional formatting (cautiously) to check for invalid data.

Exporting data
  • Data stored in common spreadsheet formats will often not be read correctly into data analysis software, introducing errors into your data.

  • Exporting data from spreadsheets to formats like CSV or TSV puts it in a format that can be used consistently by most programs.


cleaned data
data that has been manipulated post-collection to remove errors or inaccuracies, introduce desired formatting changes, or otherwise prepare the data for analysis
conditional formatting
formatting that is applied to a specific cell or range of cells depending on a set of criteria
CSV (comma separated values) format
a plain text file format in which values are separated by commas
a variable that takes on a limited number of possible values (i.e. categorical data)
data which describes other data
null value
a value used to record observations missing from a dataset
a single measurement or record of the object being recorded (e.g. the weight of a particular mouse)
plain text
unformatted text
quality assurance
any process which checks data for validity during entry
quality control
any process which removes problematic data from a dataset
raw data
data that has not been manipulated and represents actual recorded values
rich text
formatted text (e.g. text that appears bolded, colored or italicized)
a collection of characters (e.g. “thisisastring”)
TSV (tab separated values) format
a plain text file format in which values are separated by tabs
a category of data being collected on the object being recorded (e.g. a mouse’s weight)